Challenge 4 Using the data given below, calculate the linear correlation between the two variables x and y. X y 0 1 a) .794 3 7 b) .878 3 2 c) .497 1 5 4 5 d) .543 The data below shows the number of years of education beyond high school (X) and income (Y) (in tens of thousands of dollars). Calculate the correlation coefficient r. X Y 5 4 a) .956 b) .941 3 6 c) -.971 1 8 3 5 d) -.956 The following data which represent two frequency distributions for ten subjects in an attitude study. The X data are scores on an attitude-toward-education measure and the Y data are scores on an attitude-toward-wealth scale. Subject 1 2 3 4 5 6 7 8 9 10 X 6 7 8 11 12 12 12 8 10 5 Y 8 10 12 16 20 19 15 12 15 8 Compute the Pearson product-moment correlation coefficient a) .950 b) .590 c) -.784 d) -.843 e) -.905 Is there a significant relationship between attitude towards education and attitude towards wealth? a) Yes b) No Enrollment and Courses Projection This is a real world example. I need your help in helping the Registrar's office in calculating how many courses should run for the Fall '15 semester. Using enrollment and courses that ran, I need you to do two things: a) Identify the regression equation for the data to estimate the number of courses. b) If the enrollment for Fall '15 is 8,050, how many courses should be scheduled? The data below should help you with your recommendation. Enrollment Courses Fall '13 8350 1305 Fall '14 8250 1422 Fall '15 7951 1295 Fall '16 8050